| 1. |
- Bailon, R., et al.
(författare)
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Analysis of heart rate variability using time-varying frequency bands based on the respiratory frequency
- 2007
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Ingår i: Proc. IEEE Conf. Eng. Med. Biol.
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Konferensbidrag (refereegranskat)abstract
- In this paper a methodological approach for the analysis of nonstationary heart rate variability (HRV) signals using time-varying frequency bands based on respiratory frequency is presented. Spectral analysis of HRV is accomplished by means of the Smoothed Pseudo Wigner Ville distribution. Different approaches to the definition of the low frequency (LF) and high frequency (HF) bands are considered which involve respiratory information, derived either from a respiratory signal or from the ECG itself. Results are presented which derive from recordings acquired during stress testing and induced emotion experiments.
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| 2. |
- Corino, V. D. A., et al.
(författare)
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A Gaussian mixture model for time-frequency analysis during atrial fibrillation electrocardiograms
- 2007
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Ingår i: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007.. - 1557-170X. - 9781424407880 ; , s. 271-274
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Konferensbidrag (refereegranskat)abstract
- During atrial fibrillation (AF), time-frequency analysis of atrial signal has been applied to describe fibrillatory frequency trends. Recently, temporal changes in spectral shape have been investigated using the spectral profile technique. This profile is computed recursively by fitting each short-time log-spectrum to a spectral template, using amplitude scaling and frequency shifting. The purpose of the present study was to develop a Gaussian mixture model of the spectral profile in order to characterize the shape of AF waveforms. A novel index is introduced, the so-called harmonic index (HI), which reflects properties of the fundamental frequency peak and related harmonics peaks as estimated from the model. The index was tested on recordings from 9 patients with persistent AF, obtained before and after exercise testing. The HI succeeded in monitoring the response to exercise, i.e. change in the spectral profile to a less harmonic pattern, which is consistent with a reduction in AF organization (HI: 0.61±0.11 vs. 0.50±0.19, rest vs. exercise; p≪0.05).
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| 3. |
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| 4. |
- Iozzia, L., et al.
(författare)
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Atrial Impulses at the Atrioventricular Node: Arrival versus Conduction during Atrial Fibrillation
- 2015
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Ingår i: 16th Nordic-Baltic Conference on Biomedical Engineering. - Cham : Springer International Publishing. - 9783319129662 - 9783319129679 ; , s. 100-103
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Konferensbidrag (refereegranskat)abstract
- The atrioventricular (AV) node plays a central role during atrial fibrillation (AF).We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing the slower of the two AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR series using maximum likelihood estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. The aim of this study is to assess the relationship between the probability γ of an atrial impulse to arrive at the slow pathway with the probability α (used in the model) of an impulse to pass through that pathway. A theoretical equation was derived to relate α with γ and viceversa, highlighting the dependence on both refractory periods and their prolongation. Results based on simulations show that the equation was correct, with an average absolute error of 0.0034 ± 0.0008.
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| 5. |
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| 6. |
- Scotti, S., et al.
(författare)
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Automatic quantitative evaluation of emotions in E-learning applications
- 2006
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Ingår i: Annu Int Conf IEEE Eng Med Biol Proc. - 1424400325 - 9781424400324 ; , s. 1359-1362
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Konferensbidrag (refereegranskat)abstract
- The long term goal of our research is to develop a tool for recognizing human emotions during e-learning processes. This could be accomplished by combining quantitative indexes extracted from non-invasive recordings of four physiological signals: namely skin conductance, blood volume pulse, electrocardiogram and electroencephalogram. Wearable, non-invasive sensors, communicating with a PC, were applied to 30 students and data were collected during exposure to three different computer-mediated content stimuli designed to evoke specific emotional states: stress, relaxation and engagement. In this paper we describe both the general emotion evaluation algorithm, and present a preliminary results suggesting that some of the quantitative indexes may be successful in characterizing and distinguishing between the three different emotional states.
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